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MIMI KURNIA NENGSIH
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pdmbengkulu58@gmail.com
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+6281541234500
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gatotkaca@pdmbengkulu.org
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Jl. Kebun Veteran No 12, Kel. Nusa Indah Kec. Ratu Agung Kota Bengkulu
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GATOTKACA Journal (Teknik Sipil, Informatika, Mesin dan Arsitektur)
Published by Perkumpulan Dosen Muda Bengkulu
ISSN : 27752992     EISSN : 27754561     DOI : https://doi.org/10.37638/gatotkaca
Core Subject : Science, Social, Engineering,
Civil Engineering, Building, Construction & Architecture Computer Science & IT Energy Environmental Science Industrial & Manufacturing Engineering Mechanical Engineering
GATOT KACA Journal (Technic Science) established in 2020. It is a peer –reviewed international journal to be of interest and use to all those concerned with research in various fields of, or closely related to, Engineering disciplines, iNFORMATIKA. GATOT KACA Journal aims to provide a highly readable and valuable addition to the literature which will serve as an indispensable reference tool for years to come. The coverage of the journal includes all new theoretical and experimental findings in the fields of Engineering or any closely related fields. The journal also encourages the submission of critical review articles covering advances in recent research of such fields as well as technical notes.
Arjuna Subject : Teknik (semua kategori) - Teknik (Lain-Lain)
Articles 2 Documents
 1 
Search results for , issue "Vol. 3 No. 1 (2022)" : 2 Documents clear
Application Of Data Mining To Determine The Amount Of Production Using The K-Means Method (Case Study At Pt. Coca Cola Distribution Indonesia Bengkulu) Mardiana, Yessi; Kalsum, Toibah Umi
GATOTKACA Journal (Teknik Sipil, Informatika, Mesin dan Arsitektur) Vol. 3 No. 1 (2022)
Publisher : Perkumpulan Dosen Muda (PDM) Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37638/gatotkaca.v3i1.459

Abstract

This study applies Data Mining using the Clustering method to determine the amount of production based on the level of product sales at PT. Coca Cola Distribution Indonesia Bengkulu branch. The algorithm used is K-Means Clustering, where data grouped based on the same characteristics will be included in the same group and the data sets entered into the groups do not overlap. The information displayed is in the form of product data groups based on the level of sales, so that it is known the amount of production at PT. Coca Cola Distribution Indonesia which is adjusted to product clusters with high, medium and low sales levels, resulting in product clusters that could be utilized by PT. Coca Cola Distribution Indonesia in determining the number of production of the next product
Membangun Server Private Cloud Storage pada Dinas Komunikasi Informasi Statistik dan Persandian Kabupaten Lebong Aziz, Muhammad Al; Khairil, Khairil; Sapri, Sapri
GATOTKACA Journal (Teknik Sipil, Informatika, Mesin dan Arsitektur) Vol. 3 No. 1 (2022)
Publisher : Perkumpulan Dosen Muda (PDM) Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37638/gatotkaca.v3i1.450

Abstract

Lebong Regency Statistical Information Communication and Encryption Office is one of the Government Agencies which located in Lebong Regency. So far, the processing and archiving data at Statistical Information Communication and Encryption Office, Lebong Regency, has utilized applications on the computer, namely  Office Application Package. Data processing, typing, or archiving are still carried out on their laptops/computers, so if you want to share data with other employees, you must use additional media, namely flash drives or external hard drives and also email. In addition, several employees have used document archive storage in cloud storage using Google Drive. The implementation of private cloud storage at Statistical Information Communication and Encryption Office, Lebong Regency used Owncloud Server through NDLC (Network Development Life Cycle) research method approach to facilitate document/archive storage and can also simplify the process of sending documents/archives to other employees, and can be accessed anytime and anywhere via the internet. Owncloud server storage that is built is 1 TeraByte so that each user will get an average storage capacity of 20-50 GB. Based on the results of the tests that have been carried out, it can be concluded that the functionality of private cloud storage using owncloud server makes it easier for employees to carry out data processing and archiving in a structured manner. Private cloud storage can be accessed offline or online via the internet, making it easier for employees who work from home to access work data. In addition, by building private cloud storage independently, the need for the amount of storage can be adjusted because it is scalable.

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